Gaussian Belief Propagation: Theory and Application. D. Bickson. Ph.D. Thesis. Submitted to the senate of the Hebrew University of Jerusalem, October 2008. Revised July 2009. arxiv
Fault identifiction via non-parametric belief propagation. D. Bickson, D. Baron, A. Ihler, H. Avissar and D. Dolev. IEEE Tran. on Signal Processing arxiv
Distributed Sensor Selection using a Truncated Newton Method. D. Bickson and D. Dolev.
arxiv
A low density lattice decoding via non-parametric belief propagation. D. Bickson, A. Ihler
and D. Dolev. 47h Annual Allerton Conference on Communication, Control and Computing, Allerton House, Illinois,
Sept. 2009, pp. 439-446. arxivbibtex
Fixing onvergence of Gaussian belief propagation algorithm. J. K. Johnson, D.
Bickson and D. Dolev. Proc. of the International symposium on information theory (ISIT), Vol. 3, June 28 - July 3, 2009, Coex, Seoul, Korea, pp. 1674-1678.
arxivbibtex
Distributed large scale network utility maximization. D. Bickson, Y. Tock, A. Zymnis, S.
Boyd and D. Dolev. Proc. of the International symposium on information theory (ISIT), Vol. 2, June 28 - July 3, 2009, Coex, Seoul, Korea, pp. 829-833.
arxivbibtex
Gaussian belief propagation for solving systems of linear equations: theory and
application. O. Shental, D. Bickson, P.H. Siegel, J.K. Wolf and D. Dolev. Tech Report.arxivbibtex
Distributed Kalman filter via Gaussian belief propagation.
D. Bickson, O. Shental and D. Dolev, In the 46th Annual Allerton
Conference on Communication, Control and Computing, Allerton House, Illinois,
Sept. 2008, pp. 628-635.
arxivbibtex
Polynomial linear programming with Gaussian belief propagation.
D. Bickson, Y. Tock, O. Shental and D. Dolev, In the 46th Annual Allerton
Conference on Communication, Control and Computing, Allerton House, Illinois,
Sept. 2008, pp. 895-901.
arxivbibtex
Gaussian belief propagation solver for systems of linear equations. O. Shental, D.
Bickson, P. H. Siegel, J. K. Wolf, and D. Dolev, In IEEE Int. Symp. on Inform.
Theory (ISIT), Toronto, Canada, July 2008, pp. 1863 - 1867.
arxivbibtex
Gaussian belief propagation based multiuser detection. D. Bickson, O. Shental, P. H.
Siegel, J. K. Wolf, and D. Dolev, In IEEE Int. Symp. on Inform. Theory
(ISIT), Toronto, Canada, July 2008, pp. 1878-1882.
arxivbibtex
Linear Detection via Belief Propagation. Danny Bickson, Danny Dolev, Ori Shental, Paul
H. Siegel and Jack K. Wolf. In the 45th Annual Allerton Conference on Communication,
Control, and Computing, Allerton House, Illinois, Sept. 07, pp. 1207-1213.
pdfbibtex
A message-passing solver for linear systems, O. Shental, D. Bickson, P. H. Siegel, J. K. Wolf,
and D. Dolev, In Proc. Information Theory and Applications (ITA) Workshop,
San Diego, CA, USA, January 2008.
pdfbibtex
Large-Scale Applications
GraphLab: A New Parallel Framework for Machine Learning.
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, and Joseph M. Hellerstein (2010).
In the 26th Conference on Uncertainty in Artificial Intelligence (UAI), 2010.
pdfbibtex
A statistical approach to monitoring of soft-real time distributed systems. D. Bickson, G.
Gershinsky, E. Hoch and K. Shagin. In ICDCS 2009, submitted for publication. Nov. 2008.
arxivbibtex
A unifying framework for rating users and data items in Peer-to-Peer and social networks.
Danny Bickson and Dahlia Malkhi. In Peer-to-Peer Networking and Applications (PPNA)
Journal, Accepted, January 2008.
htmlbibtex
Peer–to-Peer Rating. Danny Bickson, Dahlia Malkhi and Lidong Zhou.
In the 7th IEEE Peer-to-Peer Computing, Galway, Ireland, Sept. 2007.
pdfbibtex
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines. D. Bickson,
D. Dolev and E. Yom-Tov. In the 5th European Complex Systems Conference.,Sept. 2008.
pdfbibtex
Other Resources
Presentation given by Prof. Erik Aurell from KTH (Sweden) in Workshop on Techniques and Challenges from Statistical Physics CRM@UAB, Barcelona, Obtober 2009. pdf
Source Code
LARGE SCALE/MULTICORE GAUSSIAN BP C++ CODE IS AVAILABLE as part of the GraphLab project: here.
Are you using my code? Joing our LinkedIn group
Gaussian belief propagation Matlab package gabp-src.zip
This package was downloaded aleardy more than 1,000 times! If you are using my code I will be happy to hear what are you working on and provide limited
support for the projects I find interesting.
Gaussian BP - sparse version, optimized,
tested on sparse matrices of size 0.5M x 0.5M , with 4% non zeros
gabpms.ms, run_gabpms.m
Quadratic Min-Sum algorithm - Moallemi and Van-Roy
LP/
Linear programming using GaBP (Allerton 2008 paper) arxiv
GaBP_convergence_fix/
Fixing convergence of
GaBP algorithm, mulituser detection example (ISIT 2009) arxiv
LDLC/
Low density lattice decoder (LDLC) using gaussian mixtures
NUM/
Distributd large scale network utility maximization (ISIT 2009) arxiv
ILP/
Non-parametric belief propagation (NBP) implementation via Alex Ihler's Matlab KDE toolbox.
NBP/
Non-parametric belief propagation (NBP) implementation via quantization (more efficient),
including working compressive sensing example and boolean least squares (multiuser detection) example.
This code was extensively tested in Dror Baron's compressive sensing journal paper
SS/
Distributed Sensor Selection using a Truncated Newton Method. Submitted for publication. arxiv
NBP_decoder/
Non-parametric belief propagation (NBP) decoder for low density lattice codes.
Allerton 2009. arxiv